There are simple approximated methods to extract the local weights from a pairwise comparison matrix which are row sums, inverse of column sums, arithmetic mean, and geometric mean. In this paper, first, we extend these methods to fuzzy analytic hierarchy process (FAHP) to extract the local weights as fuzzy numbers (FNs). Then, these weights are defuzzified using the center of gravity (COG) method. We also propose an approach to integrate different local weights obtained from different approximated methods to achieve a unified local weight. Moreover, this study proposes a novel and simple approach in which uncommon FNs are indirectly defuzzified based on COG method. This helps extend the multi‐attribute decision‐making methods to uncommon FNs. To illustrate the applicability of the proposed approaches, three numerical examples are given and their results are compared with some well‐known FAHP methods in the literature.

中文翻译：

---

再谈模糊层次分析法中近似权重的提取方法

有简单的近似方法可以从成对的比较矩阵中提取局部权重，这些成对的比较矩阵是行总和，列总和的倒数，算术平均值和几何平均值。在本文中，首先，我们将这些方法扩展到模糊层次分析法（FAHP），以提取局部权重作为模糊数（FNs）。然后，使用重心（COG）方法对这些权重进行解模糊。我们还提出了一种方法，可以对从不同的近似方法获得的不同局部权重进行积分，以实现统一的局部权重。此外，本研究提出了一种新颖而简单的方法，其中基于COG方法对不常见的FN进行间接去模糊处理。这有助于将多属性决策方法扩展到罕见的FN。为了说明所提出方法的适用性，